With the latest release of SAP S/4HANA 2022, SAP Master Data Governance provides you with powerful new data quality management tools.
SAP S/4HANA allows you to maintain business-important but not SAP standard information by defining custom fields. Key users can use the Custom Field app to manage these fields. For details on how to use this app see this video. Once you publish custom fields in the relevant context, you can use them in related apps and APIs.
This blog explains how the MDG Data Quality Management functions support custom fields.
This blog explains how the MDG Data Quality Management functions support custom fields.
In our example we will use the Custom Fields Fiori app to extend one field for Master Data, Product Plant, and then publish it.
Normally, if this is a new SAP S/4HANA system, before MDG is enabled, all product master data including the custom fields will be loaded or migrated from ECC into this system.The next chapter describes how these fields can be used in MDG data quality management.
Go to transaction MDCIMG and navigate to Configure Process Models and Field Properties > Configure Process Models. Determine which field has been added, select the table under the Business Object Type -(in our example, Product (194) table MARC), go to Table Fields, and choose the Synchronize Fields button in edit mode. After saving, it is ready to use in data quality management.
Navigate to the Validation Rules app for your domain. You can find the custom field on the value help list for Checked Field after the Custom field is published.
In the BRFplus expression, before you can use the custom field in rule implementation, you need to refresh the DDIC binding. Then it will be available in the context list and can be used like other attributes.
Quality checks on custom fields can be executed in consolidation and mass processing applications. In this example custom fields are checked in mass processing using the validation rule defined in the above chapter.
Besides data checking in the data change process, MDG Data Quality Management provides the quality evaluation function, which supports you in discovering erroneous master data based on your defined validation rules.
You define a periodic job or manually execute the evaluation, and the results are provided in an overview page and in the evaluation results apps.
During the evaluation, the custom fields are also evaluated. And after evaluation, the custom fields are also available in the evaluation results apps for you to review the results, and from there you can trigger the data remediation for custom fields.
In our example, after executing the data quality evaluation, the rule violation items appear in the Evaluation Results for Product Plant app, where the Custom fields can be evaluated against validation rules. The results can be filtered and displayed in the evaluation result applications and correction on custom fields can be done in a triggered mass Processing.
Once the data is corrected and after a new data quality evaluation, then the rule violation will disappear, and your data quality score on the rule is increased.
In Data Quality Management, derivation scenarios group derivation rules together to automate the value(s) of single or multiple fields. Custom fields can be used as Condition and Result fields in derivation rules.
Derivation scenarios can then be used in mass processing and consolidation, for example to automate the extension of materials to plants or to create customer data for a business partner.
Before deleting a custom field that is already in use in the data quality management apps, to avoid system inconsistency, you must remove all references to it. Examples of references include: checked fields in the validation rules app, field selection in rule mining runs, mined rules, condition and results fields in the derivation scenarios, and implementations in the BRFplus.
MDG Data Quality Management has been integrated with SAP S/4HANA extensibility using the Custom Field app. With the end-2-end example described above, you can see that a validation rule can be defined on a custom field, and these rules can be applied in data quality evaluation, mass processing, and consolidation process just like a standard field. Similarly, in automation, custom fields can be automated using derivation rules. As a customer, you will be able to manage data quality based on your own defined fields with SAP Master Data Governance.
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